"POLITEHNICA" UNIVERSITY OF TIMISOARA
SYLLABUS
for the discipline:
"ADVANCED DIGITAL SIGNAL PROCESSING"
FACULTY: AUTOMATION AND COMPUTERS
DOMAIN / SPECIALIZATION: COMPUTER ENGINEERING
Year of Studies: I or II (MASTER)
Semester: 1
Course instructor: associate professor Mihai V. Micea, PhD.
Applications instructor: associate professor Mihai V. Micea, PhD.
Number of hours/week/Evaluation/Credits
Course
Seminar
Laboratory
Project
Evaluation
2
0
0
1
Exam
Credits
9
A. COURSE OBJECTIVES
The course focuses on the advanced techniques and algorithms used in digital signal processing. Students
will learn the main design and analysis techniques of advanced types of digital filters such as: efficient
FIR and IIR filters, adaptive filters, linear prediction and optimum filters. Students will also gain abilities
of designing and implementing advanced digital signal processing algorithms and systems using generic
and specialized digital devices (Digital Signal Processors – DSPs).
B. COURSE SUBJECTS
Implementation of discrete-time systems (4 h): Structures for FIR and IIR systems; State-space system
analysis and structures; Quantization of filter coefficients; Round-off effects in digital filters. Design of
digital filters (6 h): Generic model for digital filter design; Design of FIR and IIR filters; Frequency
transformations; Design of digital filters based on Least-Squares Method. Multirate digital signal
processing (4 h): Decimation and interpolation; Sampling rate conversion; Filter design and
implementation for sampling-rate conversion; Multistage implementation of sampling-rate conversion;
Applications of multirate signal processing. Design of adaptive digital filters (6 h): Goal of adaptive
digital filtering; General concepts; Theory of Wiener-type digital filters; Adaptive LMS algorithm; LeastSquares recursive algorithm; Applications of adaptive digital filtering. Elements of spectral analysis and
estimation (4 h): Principle and traditional methods of spectral estimation; Modern methods of parametric
estimation; Applications of spectral analysis. Linear prediction and optimum linear filters (4 h):
Forward and backward linear prediction; Properties of the linear prediction – error filters; Applications of
linear prediction.
C. APPLICATIONS SUBJECTS (projects, 14 h)
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9.
Architecture and programming of the Freescale StarCore DSP system.
FFT implementation and evaluation on a PC and on the StarCore DSP.
Implementation and evaluation of FIR digital filters on a PC and on the StarCore DSP.
Implementation and evaluation of IIR digital filters on a PC and on the StarCore DSP.
Design and implementation of a digital audio effects processor.
Design and implementation of a digital audio equalizer on specialized devices (DSP).
Design, implementation and analysis of multirate systems.
Adaptive digital filters: design, implementation and evaluation.
Linear prediction filters: design, implementation and evaluation.
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D. BIBLIOGRAPHY
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G. Proakis, D. G. Manolakis, "Digital Signal Processing. Principles, Algorithms and Applications",
3rd Edition, Prentice-Hall, 1996.
A. V. Oppenheim, R. W. Schafer, "Digital Signal Processing", Prentice-Hall, 1996.
S. Stergiopoulos (editor), "Advanced Signal Processing Handbook: Theory and Implementation for
Radar, Sonar, and Medical Imaging Real-Time Systems", CRC Press LLC, 2001.
E. EVALUATION PROCEDURE
The final grade is composed of the evaluation during the semester at the project workshops and at the
course classes (50%), and of the final written exam evaluation (3 hours, 50%).
F. INTERNATIONAL COMPATIBILITY
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Massachusetts Institute of Technology, SUA, Department of Electrical Engineering and Computer
Science, Basic Undergraduate Program: "Discrete-Time Signal Processing" (6.341, A. V.
Oppenheim, V. K. Goyal), "Digital Speech Processing" (6.343, T. F. Quatieri), "Introduction to
Communication, Control, and Signal Processing" (6.011, A. V. Oppenheim, G. C. Verghese)
Carnegie Mellon University, SUA, Department of Electrical and Computer Engineering,
Undergraduate Program: "Advanced Digital Signal Processing" (18-792), "Digital Signal
Processing" (18-491), "Digital Communication and Signal Processing Systems Design" (18-551)
University of Cambridge, UK, Department of Engineering, Undergraduate Program: "Digital
Filters and Spectrum Estimation" (4F7, S. J. Godsill, S. Singh), "Signals and Systems" (3F1, J.M.
Goncalves, N.G. Kingsbury), "Signal and Pattern Processing" (3F3, S. J. Godsill)
G. OBSERVATIONS
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The course is presented using PowerPoint slides with a video projector. Students can receive the
course support (course slides) in electronic or printed format.
The project and application workshops will be hosted by the Digital Signal Processing Laboratories
– DSPLabs, which provides latest generation equipments and specialized modules through various
partnerships with top-ranking companies in the domain, such as: Motorola/Freescale, AlcatelLucent, etc.
Interested students have the opportunity to collaborate at various projects and research contracts,
developed within the DSPLabs. Such participation replaces the applicative activities required by the
syllabus.
26.03.2007
HEAD OF DEPARTMENT
Prof. Dr. Eng. Vladimir CRETU
COURSE INSTRUCTOR,
Assoc.Prof. Dr. Eng. Mihai V. MICEA
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